The Graph500 benchmark attempts to steer the design of High-Performance Computing systems to maximize the performance under memory-constricted application workloads. A realistic simulation of such benchmarks for architectural research is challenging due to size and detail limitations. By contrast, synthetic traffic workloads constitute one of the least resource-consuming methods to evaluate the performance. In this work, we provide a simulation tool for network architects that need to evaluate the suitability of their interconnect for BigData applications. Our development is a low computation- and memory-demanding synthetic traffic model that emulates the behavior of the Graph500 communications and is publicly available in an open-source network simulator. The characterization of network traffic is inferred from a profile of several executions of the benchmark with different input parameters. We verify the validity of the equations in our model against an execution of the benchmark with a different set of parameters. Furthermore, we identify the impact of the node computation capabilities and network characteristics in the execution time of the model in a Dragonfly network

The authors would like to thank the European HiPEAC Network of Excellence for partially funding this work through a Collaboration Grant. They would like to thank as well Crist´obal Camarero for his help. This work has been supported by the Spanish Ministry of Education, FPU grants FPU13/00337 and FPU14/02253, the Spanish Ministry of Economy, Industry and Competitiveness under contract TIN2016-76635-C2-2-R (AEI/FEDER, UE), and by the Mont-Blanc project. The Mont-Blanc project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 671697. Santander Supercomputacion support group from the University of Cantabria provided access to the Altamira Supercomputer at the Institute of Physics of Cantabria (IFCA-CSIC).

Peer Reviewed